The relationship between Neisseria gonorrhoeae diagnosis and the timing of HIV transmission events: a molecular epidemiology study

Abstract Background Diagnoses of sexually transmitted infections (STIs), such as Neisseria gonorrhoeae (NG), are key entry points to HIV services, including linkage to pre-exposure prophylaxis. Understanding whether bacterial STI-associated clinical encounters effectively interrupt onward HIV transmission is crucial for evaluating the robustness of integrated prevention systems. Methods We analyzed 1,866 HIV-1 subtype B pol sequences collected in a high HIV and NG prevalence setting of Miami-Dade County, Florida (2015-2022), and linked them with NG diagnosis records. A time-scaled maximum-likelihood phylogeny was reconstructed, and “young” clades (<2 years old) were identified as proxies for recent HIV transmissions. We evaluated whether any of the “young” clades included at least one individual diagnosed with NG within one year prior to the clade’s time to the most recent common ancestor (clade origination event), and compared annual proportions of such clades to permutation-based “expected” distributions derived from randomizing NG diagnoses across the HIV phylogeny. Results Among 49 “young” clades, 14 (28.6%) included a recent NG diagnosis. Whereas most years showed no difference from null expectations, 2020 had a higher proportion of “young” clades with a recent NG diagnosis (p = 0.01), coinciding with COVID-19-related service disruptions. In 2021, no “young” clades had recent NG diagnoses (p = 0.04), consistent with reduced STI testing during 2020. “Young” clades with recent NG diagnoses also had a higher than expected proportion of Hispanic individuals (p = 0.02). Conclusions By linking HIV molecular data with routine STI diagnoses, we observed a temporal pattern consistent with disruption of STI-linked HIV prevention services during the height of the COVID-19 epidemic and the associated healthcare disruption. Integrating molecular epidemiology with routine STI surveillance provides a scalable public health approach to monitoring the performance and robustness of linked STI prevention systems.